Identifying neurocognitive heterogeneity in Older Adults with Bipolar Disorder: a cluster analysis

dc.contributor.authorMontejo Egido, Laura
dc.contributor.authorJiménez Martínez, Ester
dc.contributor.authorSolé Cabezuelo, Brisa
dc.contributor.authorMurru, Andrea
dc.contributor.authorArbelo, Néstor
dc.contributor.authorBenabarre, Antonio
dc.contributor.authorValentí Ribas, Marc
dc.contributor.authorClougher, Derek
dc.contributor.authorRodríguez, M.A.
dc.contributor.authorBorràs, Roger
dc.contributor.authorMartínez-Arán, Anabel, 1971-
dc.contributor.authorVieta i Pascual, Eduard, 1963-
dc.contributor.authorBonnín Roig, Caterina del Mar
dc.contributor.authorTorrent Font, Carla
dc.date.accessioned2026-01-15T09:36:31Z
dc.date.available2026-01-15T09:36:31Z
dc.date.issued2022-02-01
dc.date.updated2026-01-15T09:36:31Z
dc.description.abstractBackground: Cognitive profiles of BD patients show a demonstrated heterogeneity among young and middle-aged patients, but this issue has not yet deeply explored in Older Adults with bipolar disorder (OABD). The aim of the present study was to analyze cognitive variability in a sample of OABD. Methods: A total of 138 OABD patients and 73 healthy controls were included in this study. A comprehensive neuropsychological assessment was administered. We performed a k-means cluster analysis method based on the neurocognitive performance to detect heterogeneous subgroups. Demographic, clinical, cognitive and functional variables were compared. Finally, univariate logistic regressions were conducted to detect variables associated with the severity of the cognitive impairment. Results: We identified three distinct clusters based on the severity of cognitive impairment: (1) a preserved group (n = 58; 42%) with similar cognitive performance to HC, (2) a group showing mild cognitive deficits in all cognitive domains (n = 64; 46%) and, finally, (3) a group exhibiting severe cognitive impairment (n = 16; 12%). Older age, late onset, higher number of psychiatric admissions and lower psychosocial functioning were associated with the greatest cognitive impairment. Lower age, more years of education and higher estimated IQ were associated with a preserve cognitive functioning. Limitations: The small sample size of the severely impaired group. Conclusions: Cognitive heterogeneity remains at late-life bipolar disorder. Demographic and specific illness factors are related to cognitive dysfunction. Detecting distinct cognitive subgroups may have significant clinical implications for tailoring specific intervention strategies adapted to the level of the impairment and also to prevent cognitive decline.
dc.format.extent71 p.
dc.format.mimetypeapplication/pdf
dc.identifier.idgrec717056
dc.identifier.issn0165-0327
dc.identifier.pmid34788686
dc.identifier.urihttps://hdl.handle.net/2445/225523
dc.language.isoeng
dc.publisherElsevier B.V.
dc.relation.isformatofVersió postprint del document publicat a: https://doi.org/10.1016/j.jad.2021.11.028
dc.relation.ispartofJournal of Affective Disorders, 2022, vol. 298, num.Part A, p. 522-531
dc.relation.urihttps://doi.org/10.1016/j.jad.2021.11.028
dc.rightscc-by-nc-nd (c) Elsevier B.V., 2022
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject.classificationCognició
dc.subject.classificationTrastorn bipolar
dc.subject.classificationNeuropsicologia
dc.subject.classificationAnàlisi de conglomerats
dc.subject.otherCognition
dc.subject.otherManic-depressive illness
dc.subject.otherNeuropsychology
dc.subject.otherCluster analysis
dc.titleIdentifying neurocognitive heterogeneity in Older Adults with Bipolar Disorder: a cluster analysis
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/acceptedVersion

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